Checking Distribution for Variables

Plot and fit distributions of variables

Histogram of Velocity of all

Log distribution, 0’s make up 3% of all data

CC.TotalData <- na.omit(TotalData)
head(CC.TotalData)

10^mean(log10(CC.TotalData$v[CC.TotalData$v>0]))

[1] 0.0348809

sd(log10(CC.TotalData$v[CC.TotalData$v>0]))

[1] 0.5467087

Now we’re going to plot each unique krill and their bimodality with a dip test (less than 0.05 is multimodality)

Starting to look at bimodality in the variables by merging the TotalData frame with the “tab” table

Now looking at turning angles

for (i in 1:length(ind)){
plot(CC.TotalData$turn.angle[CC.TotalData$D_V_T==ind[i]], log10(CC.TotalData$v[CC.TotalData$D_V_T==ind[i]]),
            xlab = "Turn Angles",
     ylab = "Velocity",
          main = "") 
}

NA

save.image("~/Post-doc/Data/Total Merged Data File.RData")